CIE LAB color space and K-means clustering algorithm for segmenting remote sensing images
Other Title(s)
فضاء الألوان CIELABً و خوارزمية العناقيد K-means لتقطيع صور الاستشعار عن بعد
Joint Authors
al-Qabba, Abd al-Rahman Rashid
al-Barhawi, Diya Hazim
Source
College of Basic Education Researches Journal
Issue
Vol. 16, Issue 1 (31 Dec. 2019), pp.2961-2970, 10 p.
Publisher
University of Mosul College of Basic Education
Publication Date
2019-12-31
Country of Publication
Iraq
No. of Pages
10
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Abstract EN
Remote sensing images contain several types of geological phenomena such as mountains, valleys, rivers, and faults, which require a considerable effort to accurately identify them from digital satellite imagery and use them in topographic mapping.
There exists big importance of the automatic segmentation methods of the remotely sensed color images.
Segmenting stage is considered as an initial stage in processing and analysis, topographic and land use mapping effectively and accurately, and any mistake at this stage has significant impacts on the rest of the subsequent stages of image processing such as extraction, classification and interpretation.-
American Psychological Association (APA)
al-Qabba, Abd al-Rahman Rashid& al-Barhawi, Diya Hazim. 2019. CIE LAB color space and K-means clustering algorithm for segmenting remote sensing images. College of Basic Education Researches Journal،Vol. 16, no. 1, pp.2961-2970.
https://search.emarefa.net/detail/BIM-1036462
Modern Language Association (MLA)
al-Qabba, Abd al-Rahman Rashid& al-Barhawi, Diya Hazim. CIE LAB color space and K-means clustering algorithm for segmenting remote sensing images. College of Basic Education Researches Journal Vol. 16, no. 1 (2019), pp.2961-2970.
https://search.emarefa.net/detail/BIM-1036462
American Medical Association (AMA)
al-Qabba, Abd al-Rahman Rashid& al-Barhawi, Diya Hazim. CIE LAB color space and K-means clustering algorithm for segmenting remote sensing images. College of Basic Education Researches Journal. 2019. Vol. 16, no. 1, pp.2961-2970.
https://search.emarefa.net/detail/BIM-1036462
Data Type
Journal Articles
Language
English
Notes
Record ID
BIM-1036462